The present invention relates to the field of near infrared spectrometry for predicting patient blood glucose levels.
There are roughly four million people in the United States currently diagnosed with Diabetes Mellitus. This disease causes blindness, loss of extremities, heart failure, and other complications over time. There is no xe2x80x9ccurexe2x80x9d for the disease, which is caused by either the failure of the pancreas to produce insulin or the body""s inability to use insulin, but rather only treatment, most commonly with insulin injections in order to change the blood-glucose level.
The majority of patients with Type I diabetes, as well as people with Type II diabetes or diagnosed as pre-diabetic, need to frequently monitor their blood glucose levels, establishing an individual blood glucose profile in order to adjust diet, medication, exercise, or to lower the blood glucose while avoiding hypoglycemia (low blood-sugar). In well-regulated patients, two or three blood samples are tested for glucose daily and are usually sufficient. In new or difficult patients, or when monitoring for hypoglycemia is required, blood samples may be required in rapid (every few minutes) succession.
Tests for blood glucose levels consist of obtaining blood by venipuncture or pricking an extremity (usually a finger) to draw a drop of blood. This blood sample is inserted into an analytical device (e.g., Accu-Check(copyright), Hemo-Cue(copyright), Diasensor 1000(copyright), Coming Express 550(copyright), Roche Cobas Mira(copyright), or Ektachem (R)DT60II Analyzer(copyright)). The device may be an electrochemical detector that monitors reaction of glucose oxidase with glucose in the blood. The current or voltage is measured, and resulting data is displayed as a concentration, typically milligrams per deciliter (mg/dL). Another means of measuring glucose is by measuring the absorbance of the reaction at 540 nm. It is often difficult, particularly in elderly or infant patients, to perform the necessary measurement, particularly when needed several times a day.
As a result, a need has developed for non-invasive techniques useable in predicting the concentration of blood glucose in the bloodstream of a patient. In this regard, a significant number of researchers have attempted over the past few decades to develop non-invasive glucose monitors using near-infrared (NIR) spectrometers.
Infrared spectrometry is a technique that is based upon the vibrational changes of the atoms of a molecule. In accordance with infrared spectrometry, an infrared spectrum is generated by transmitting infrared radiation through a sample of an organic substance and determining the portions of the incident radiation that are absorbed by the sample. An infrared spectrum is a plot of absorbance (or transmittance) against wavenumber, wavelength or frequency. Infrared radiation is radiation having a wavelength between about 750 nm and about 1000 xcexcm. Near-infrared radiation is radiation having a wavelength between about 750 nm and about 2500 nm.
A variety of different types of spectrometers are known in the art such as grating spectrometers, FT (Fourier transformation) spectrometers, Hadamard transformation spectrometers, AOTF (Acousto Optical Tunable Filter) spectrometers, diode array spectrometers, filter-type spectrometers, scanning dispersive spectrometers and nondispersive spectrometers.
Filter-type spectrometers, for example, utilize an inert solid heated to provide continuous radiation (e.g., tungsten filament lamp) to illuminate a rotating opaque disk, wherein the disk includes a number of narrow bandpass optical filters. The disk is then rotated so that each of the narrow bandpass filters passes between the light source and the sample. An encoder indicates which optical filter is presently under the light source. The filters filter light from the light source so that only a narrow selected wavelength range passes through the filter to the sample. Optical detectors are positioned so to as detect light that either is reflected by the sample (to obtain a reflectance spectra) or is transmitted through the sample (to generate a transmittance spectra). The amount of detected light is then measured and provides an indication of the amount of absorbance of the light by the substance under analysis.
Diode Array spectrometers use infrared emitting diodes (IREDs) as sources of near-infrared radiation. A plurality of (for example, eight) IREDs are arranged over a sample work surface to be illuminated for quantitative analysis. Near-infrared radiation emitted from each IRED impinges upon an accompanying optical filter. Each optical filter is a narrow bandpass filter that passes NIR radiation at a different wavelength. NIR radiation passing through the sample is detected by a detector (such as a silicon photodetector). The amount of detected light is then measured and provides an indication of the amount of absorbance of the light by the substance under analysis.
Acousto Optical Tunable Filter spectrometers utilize an RF signal to generate acoustic waves in a TeO2 crystal. A light source transmits a beam of light through the crystal, and the interaction between the crystal and the RF signal splits the beam of light into three beams: a center beam of unaltered white light and two beams of monochromatic and orthogonally polarized light. A sample is placed in the path of one of the monochromatic beam detectors, which are positioned to detect light that either is reflected by the sample (to obtain a reflectance spectra) or is transmitted through the sample (to generate a transmittance spectra). The wavelength of the light source is incremented across a wavelength band of interest by varying the RF frequency. The amount of detected light is then measured and provides an indication of the amount of absorbance of the light by the substance under analysis.
In grating monochromator spectrometers, a light source transmits a beam of light through an entrance slit and onto a diffraction grating (the dispersive element) to disperse the light beam into a plurality of beams of different wavelengths (i.e., a dispersed spectrum). The dispersed light is then reflected back through an exit slit onto a detector. By selectively altering the path of the dispersed spectrum relative to the exit slit, the wavelength of the light directed to the detector can be varied. The amount of detected light is then measured and provides an indication of the amount of absorbance of the light by the substance under analysis. The width of the entrance and exit slits can be varied to compensate for any variation of the source energy with wavenumber.
A nondispersive infrared filter photometer is designed for quantitative analysis of various organic substances. The wavelength selector comprises: a filter as previously described to control wavelength selection; a source; and a detector. The instrument is programmed to determine the absorbance of a multicomponent sample at wavelengths and then to compute the concentration of each component.
As stated above, spectrometers have been used to measure the chemical composition of blood and, more particularly, blood glucose. The mean blood glucose level varies within a normal range of 70-120 mg/dL from person to person. For diabetics, these fluctuations can vary markedly, reaching values of 200-400 mg/dL within a very short time in accordance with their food intake, physical activity, a complication by another disease, or the like. The majority of patients with Type I diabetes, as well as people with Type II diabetes or diagnosed as pre-diabetic, need to frequently monitor their blood glucose levels, establishing an individual blood glucose profile in order to adjust diet, medication or exercise, or in order to lower the blood glucose while avoiding hypoglycemia (low blood-sugar). In well-regulated patients, two or three blood samples are tested for glucose daily and are usually sufficient. In new or difficult patients, or when monitoring for hypoglycemia is required, blood samples may be required in rapid (every few minutes) succession.
The major problems with non-invasive NIR blood glucose monitors are the high operating cost, a lack of reproducible results and difficulty in use. Hand-held instruments for home use fail in that the instruments do not consistently provide the correct assessment of blood glucose concentration over the entire length of time the instruments are used. These hand-held devices are calibrated with a one-time global modeling equation hard-wired into the instrument, to be used by all patients from time of purchase onward. The model does not provide for variations in the unique patient profile which includes such factors as gender, age or other existing disease states.
For example, U.S. Pat. No. 5,961,449 to Toida et al. purports to disclose a method and apparatus for non-invasive measurement of the concentration of glucose in the aqueous humor in the anterior aqueous chamber of the eyeball, and a method and apparatus for non-invasive measurement of the concentration of glucose in the blood in accordance with the concentration of glucose in the aqueous humor. Known near-infrared analytical techniques using multivarient analysis are utilized therein.
A number of patents including U.S. Pat. Nos. 5,703,364, 5,028,787, 5,077,476 and 5,068,536, all to Rosenthal, purport to describe an at-home testing near-infrared quantitative analysis instrument and method of non-invasive measurement of blood glucose by measuring near-infrared energy following interaction with venous or arterial blood or following transmission through a blood-containing body part. Questions have been raised about the accuracy of the instrument described in these patents and, to date, FDA approval for such an instrument has not been attained.
U.S. Pat. No. 5,574,283 to Quintana purports to describe a near-infrared quantitative analysis instrument for measuring glucose comprising an analysis instrument having a removable insert that facilitates positioning of an individual user""s finger within the instrument according to the size of the user""s finger.
U.S. Pat. No. 5,910,109 to Peters et al. allegedly describes a glucose measuring device for determining the concentration of intravascular glucose in a subject including: a light source having a wavelength of 650, 880, 940 or 1300 nm to illuminate the fluid; receptors associated with the light sources for receiving light and generating a transmission signal representing the light transmitted and adapted to engage a body part of a subject; and a signal analyzer, which includes a trained neural network for determining the glucose concentration in the blood of the subject. This reference purportedly also provides a method for determining the glucose concentration, which method includes calibration of a measuring device and setting of an operating current for illuminating the light sources during operation of the device. According to this patent, when a transmission signal is generated by receptors, the high and low values from each of the signals are stored in the device and are averaged to obtain a single transmission value for each of the light sources. The averaged values are then analyzed to determine the glucose concentration, which then is displayed.
U.S. Pat. No. 5,935,062 to Messerschmidt et al. purports to describe a specular control device that can discriminate between diffusely reflected light that is reflected from selected depths or layers within the tissue by receiving the diffusely reflected light that is reflected from a first layer or depth within the tissue, while preventing the remaining diffusely reflected light from reaching the spectroscopic analyzer. This patent allegedly describes a method for obtaining diffuse reflectance spectra from human tissue for the non-invasive measurement of blood analytes, such as blood glucose by collecting the infrared energy that is reflected from a first depth and rejecting the infrared energy that is reflected from a second.
U.S. Pat. No. 5,941,821 to Chou allegedly provides an apparatus for more accurate measurement of the concentration of a component in blood (e.g., glucose), including a source for irradiating a portion of the blood by heat-diffusion to generate acoustic energy propagating in a second medium over a surface of the blood in response to the irradiation, a detector for detecting the acoustic energy and for providing an acoustic signal in response to the acoustic energy, and a processor for determining the concentration of the component in response to the acoustic signal and characteristics of the component.
In all spectroscopic techniques, including those discussed above, calibration samples must be run before an analysis is conducted. In NIR spectroscopy, a modeling equation (often referred to as a calibration model) that reflects the individual patient""s blood glucose profile is generated by scanning a number of blood glucose samples to generate a set of calibration data, and then processing the data to obtain the modeling equation.
In a static system with little interference, this calibration is required only once, and spectral prediction can be conducted without the need to rerun calibration samples. In the real world, this is an infrequent occurrence. Most systems that require study are dynamic and require frequent recalibration. The recalibration procedure involves scanning a set of calibration samples and analyzing those same samples with a primary technique, such as High Performance Liquid Chromatography (HPLC), to adjust the modeling equation.
In previous attempts to develop a near IR spectral device for blood glucose determination, a single static modeling equation was generated using a statistical population of test subjects. This single modeling equation was then xe2x80x9chardwiredxe2x80x9d into the spectral sensing device and used for all test subjects. This has proven to be problematic since people display blood chemistry within a wide range of normal values, or abnormal values in the case of a disease state (e.g., diabetes), due to each person""s combinations of water level, fat level and protein level, each of which cause variations in energy absorption. The variations in these constituents between different people make a universal calibration for diabetes patients unlikely, particularly because the amount of glucose in the body is less than one thousandth of these other constituents.
U.S. Pat. No. 5,507,288 to Bocker et al. purportedly describes a non-invasive portable sensor unit combined with an invasive analytical system that can contain an evaluation instrument capable of calibrating the results of the non-invasive system. The evaluation instrument of this patent contains only one calibration equation, and the disclosure does not contemplate recalculation of the equation or recalibration of the evaluation instrument over time. This can be problematic, since, because a patient""s blood chemistry changes with time, the xe2x80x9cpermanentxe2x80x9d calibration slowly, or even rapidly, begins giving incorrect predictions. Thus, the ability to correctly assess the amount of blood glucose deteriorates over time.
Throughout this application, various patents and publications are referred to. Disclosure of these publications and patents in their entirety are hereby incorporated by reference into this application to more fully describe the state of the art to which this invention pertains. In particular, the disclosure of commonly-owned and co-pending U.S. patent application Ser. No. 09/636,041, entitled Automated System And Method for Spectroscopic Analysis and filed on Aug. 10, 2000, is hereby incorporated by reference.
In order to accurately predict blood glucose levels using a noninvasive spectroscopic technique, a dynamic modeling equation is needed. A dynamic modeling equation is one that provides a way to recalculate the equation when the model no longer accurately reflects the patient""s glucose profile. A dynamic model is accomplished by scanning the subject with a noninvasive spectroscopic blood glucose monitor and then using an invasive technique (e.g., venipuncture or a fingerstick) to obtain a constituent value to associate with the spectral data. This procedure must be repeated a number of times in order to obtain a sufficient number of spectral data scans and associated constituent values to develop a robust and accurate modeling equation for the individual patient. The frequency and amount of recalibration needed is dependent on the amount of variation in the individual subject""s blood glucose values. To recalibrate, additional spectral scans and associated constituent values are obtained from the patient, and the modeling equation is regenerated using the original data along with the new data. In cases where the original data is found to be unsuitable (for example, due to significant change in the patient""s condition), it may be necessary to discard the original data and obtain a fall set of new spectral scans and associated constituent values. However, even if this recalibration is required on a weekly basis, a significant reduction in the amount of invasive monitoring has been achieved.
A truly dynamic modeling equation would seemingly require a highly trained and experienced individual using an advanced statistics computer program to evaluate the modeling equation and to perform the mathematics required to maintain the modeling equation. It is impractical, however, to have a scientist directly consult with each patient to maintain his or her individual modeling equation. This is especially true if development of a hand-held, remote spectral device for home use is desired.
Although many attempts have been made to construct a spectral device that will monitor the amount of blood glucose in a non-invasive manner, some of which are discussed above, a major shortcoming in each of these previous attempts has been in the development of a robust dynamic modeling equation for the prediction of bloodglucose levels.
In accordance with the present invention, a dynamic modeling equation is provided that can predict the patient""s blood glucose level using a noninvasive spectral scan obtained from a remote spectral device (preferably handheld). A spectral scan is obtained from a patient and sent to a central computer. A central computer stores the generated spectral scan along with a previously generated patient modeling equation for that patient. A resultant blood glucose level is calculated for that patient based on his or her individual modeling equation. If the spectral scan falls within the range of the modeling equation, a blood glucose value is predicted and the predicted blood glucose level is output to the patient. If the spectral scan falls outside the range of the modeling equation, regeneration of the model is required, and the patient is instructed to take a number of noninvasive scans, followed by an invasive blood glucose level determination. All of the data is then transferred to the central computer where the modeling equation is regenerated based on both the existing data points and the new data points. A preferred method for generating and updating the modeling equation is set forth in more detail below.
Preferably, the central computer uses a complex statistics computer program to generate a new modeling equation, thereby allowing for much of this task to be automated. A new modeling equation is generated as needed, for example in cases of a change in medical condition that affects the blood glucose levels or as instructed by the manufacturer (e.g., once a month).
The remote spectral device communicates with the central computer by any conventional mode of data transmission, such as a cellular data link, a telephone modem, a direct satellite link, or an Internet link. The remote spectral device may be directly linked to the invasive blood glucose monitor by an appropriate data connection, such as an RS233 data connection, but preferably both the sensor and monitor are contained in the same unit along with a handheld computer, similar to a PALM PILOT(trademark). In certain embodiments, additional messages can be sent from the central computer to the remote spectral device, for example, reminders to the patient to obtain blood glucose levels or to take medication. It may also be desirable to include other data inputs from the patient, such as blood pressure, heart rate and temperature, which data will be transmittable from the remote spectral device to the central computer.
In further embodiments, the central processing unit further communicates the relevant information received from the patient and any instructions transmitted to the patient via the remote spectral device to the patient""s doctor or hospital.
In one embodiment of the present invention, there is provided a method for predicting blood glucose values in a patient by: generating an individualized modeling equation for a patient as a function of non-invasive spectral scans of a body part of the patient and an analysis of blood samples from the patient, and storing the individualized modeling equation on a central computer; receiving from the patient a non-invasive spectral scan generated by a remote spectral device; predicting a blood glucose value for the patient as a function of the non-invasive spectral scan and the individualized modeling equation, and transmitting the predicted blood glucose value to the patient; determining that a regeneration of the individualized modeling equation is required, and transmitting a request for a set of non invasive spectral scans and a corresponding set of blood glucose values to the patient; acquiring a set of noninvasive spectral scans from the patient using the remote spectral device and a corresponding set of blood glucose values from a remote invasive blood glucose monitor; transmitting the set of spectral scans and corresponding blood glucose values to the central computer; and regenerating the individualized modeling equation as a function of the set of spectral scans and corresponding blood glucose values.